Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan.
Department of Urology, Hokkaido University Graduate School of Medicine, North-15, West-7, North Ward, Sapporo, 060-8638, Japan.
Surg Endosc. 2021 Aug;35(8):4399-4416. doi: 10.1007/s00464-020-07940-7. Epub 2020 Sep 9.
Our aim was to characterize the motions of multiple laparoscopic surgical instruments among participants with different levels of surgical experience in a series of wet-lab training drills, in which participants need to perform a range of surgical procedures including grasping tissue, tissue traction and dissection, applying a Hem-o-lok clip, and suturing/knotting, and digitize the level of surgical competency.
Participants performed tissue dissection around the aorta, dividing encountered vessels after applying a Hem-o-lok (Task 1), and renal parenchymal closure (Task 2: suturing, Task 3: suturing and knot-tying), using swine cadaveric organs placed in a box trainer under a motion capture (Mocap) system. Motion-related metrics were compared according to participants' level of surgical experience (experts: 50 ≤ laparoscopic surgeries, intermediates: 10-49, novices: 0-9), using the Kruskal-Wallis test, and significant metrics were subjected to principal component analysis (PCA).
A total of 15 experts, 12 intermediates, and 18 novices participated in the training. In Task 1, a shorter path length and faster velocity/acceleration/jerk were observed using both scissors and a Hem-o-lok applier in the experts, and Hem-o-lok-related metrics markedly contributed to the 1st principal component on PCA analysis, followed by scissors-related metrics. Higher-level skills including a shorter path length and faster velocity were observed in both hands of the experts also in tasks 2 and 3. Sub-analysis showed that, in experts with 100 ≤ cases, scissors moved more frequently in the "close zone (0 ≤ to < 2.0 cm from aorta)" than those with 50-99 cases.
Our novel Mocap system recognized significant differences in several metrics in multiple instruments according to the level of surgical experience. "Applying a Hem-o-lok clip on a pedicle" strongly reflected the level of surgical experience, and zone-metrics may be a promising tool to assess surgical expertise. Our next challenge is to give completely objective feedback to trainees on-site in the wet-lab.
我们的目的是在一系列湿实验室培训中描述具有不同手术经验水平的参与者使用多种腹腔镜手术器械的运动情况,参与者需要在这些训练中执行一系列手术程序,包括抓取组织、组织牵引和解剖、应用 Hem-o-lok 夹以及缝合/打结,并对手术能力水平进行数字化。
参与者在运动捕捉(Mocap)系统下的盒子训练器中使用猪尸体器官进行主动脉周围的组织解剖,在应用 Hem-o-lok 后分离遇到的血管(任务 1),以及肾脏实质闭合(任务 2:缝合,任务 3:缝合和打结)。根据参与者的手术经验水平(专家:腹腔镜手术≥50 例、中级:10-49 例、新手:0-9 例)比较运动相关指标,采用 Kruskal-Wallis 检验,显著指标进行主成分分析(PCA)。
共有 15 名专家、12 名中级和 18 名新手参加了培训。在任务 1 中,专家使用剪刀和 Hem-o-lok 施夹器时,路径长度更短,速度/加速度/冲击更快,Hem-o-lok 相关指标在 PCA 分析的第一主成分中贡献显著,其次是剪刀相关指标。在任务 2 和 3 中,专家双手也表现出更高水平的技能,包括更短的路径长度和更快的速度。亚分析显示,在手术例数≥100 例的专家中,剪刀在“关闭区(0≤至<2.0 厘米距离主动脉)”中比手术例数 50-99 例的专家更频繁地移动。
我们的新型 Mocap 系统根据手术经验水平识别了多种器械中多个指标的显著差异。“在蒂上应用 Hem-o-lok 夹”强烈反映了手术经验水平,区域指标可能是评估手术技能的有前途的工具。我们的下一个挑战是在湿实验室现场为学员提供完全客观的反馈。